Back to Search Start Over

Study of Thermal Compression Constitutive Relation for 5182-Sc-Zr Alloy Based on Arrhenius-Type and ANN Model.

Authors :
Li, Jingxiao
Yang, Xiaofang
Zhu, Yulong
Zhang, Yongfa
Qiu, Youcai
Sanders Jr., Robert Edward
Source :
Crystals (2073-4352); May2022, Vol. 12 Issue 5, pN.PAG-N.PAG, 21p
Publication Year :
2022

Abstract

Hot compression experiments were performed on alloy 5182 with small additions of Sc and Zr. The 5182 alloy containing Sc and Zr is critical for expanding the 5182 alloy's range of applications, and a thorough understanding of its thermal processing behavior is of great importance to avoid processing defects. Alloy microstructure, including grain structures and Al<subscript>3</subscript>(Sc<subscript>x</subscript>Zr<subscript>1−x</subscript>) dispersoids were analyzed by EBSD and TEM. Stable flow stresses were observed below a strain rate of 1 s<superscript>−1</superscript> for the Sc-Zr containing alloy. The results of constitutive models, with and without strain−compensation, and artificial neural network (ANN) were used to compare to the experimental results. The Al<subscript>3</subscript>(Sc<subscript>x</subscript>Zr<subscript>1−x</subscript>) dispersoid data was introduced into the ANN model as a nonlinear influence factor. Addition of the Al<subscript>3</subscript>(Sc<subscript>x</subscript>Zr<subscript>1−x</subscript>) dispersoid information as input data improved the accuracy and practicality of the artificial neural network in predicting the deformation behavior of the alloy. The squared correlation coefficients of ANN prediction data reached 0.99. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20734352
Volume :
12
Issue :
5
Database :
Complementary Index
Journal :
Crystals (2073-4352)
Publication Type :
Academic Journal
Accession number :
157191561
Full Text :
https://doi.org/10.3390/cryst12050611